---
title: "Custom Parameters"
description: "Custom parameters allow users to add extra metadata that is specific to their
  workflow which is common among LLM developers. Adding custom parameters help
  our users a bunch with"
---

### Possible parameters

`Helicone-Prompt-ID`: Unique identifier for this prompt. (ex:
"wedding-cards-001")

`Helicone-Request-ID`: A user specified UUID for that request. (Must be a
uuidv4)

`Helicone-User-ID`: Any string representation of your user. (ex:
"fred@example.com")

### Adding a custom parameter to your query

<Tabs>

<Tab title="Curl" >

You can simply add those as headers like this

```
  -H 'Helicone-Prompt-ID: "wedding-cards-001"'
  -H 'Helicone-User-ID: "fred@example.com"'
```

</Tab>

<Tab title="Node.js">

In your OpenAI configuration, you can add an extra argument called `baseOptions`
and include the custom parameter has a header.

```javascript
import { Configuration, OpenAIApi } from "openai";
dfkljd;
const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
  basePath: "https://oai.hconeai.com/v1",
  baseOptions: {
    headers: {
      "Helicone-Prompt-ID": "wedding-cards-001",
      "Helicone-User-ID": "fred@example.com",
    },
  },
});
const openai = new OpenAIApi(configuration);
```

</Tab>

</Tabs>
